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# Senior Applied AI Scientist

- **Company:** DeepRec
- **Location:** London, UK (Remote available)
- **Experience:** Expert
- **Contract:** Permanent contract
- **Skills:** Artificial Intelligence, Amazon Web Services, Artificial Neural Networks, Big Data, Cloud Computing, Python (Programming Language), Machine Learning, Tensorflow, Systems Integration, Pytorch, Gaussian, Information Technology, Dask
- **Published:** September 10, 2026
- **Apply:** https://www.collegerecruiter.com/job/2840580434-senior-applied-ai-scientist

## About the Role

* Strong background in applied machine learning, bayesian statistics, and causal inference.
 * Proficiency in Python and ML frameworks such as PyTorch.
 * Experience with cloud infrastructure (e.g., AWS, GCP).
 * A clear, concise communication style - clear examples given when asked, not word salad.
 * An adaptive mindset and comfort working in fast-changing environments.
 * A deep motivation to contribute to climate and ecological impact.
 * An advanced degree (MSc or PhD) in Computer Science, Statistics, Economics, Physics, Mathematics, or a related field., * Experience working with geospatial or spatial-temporal data.
 * Experience with remote sensing datasets (e.g., Landsat, Sentinel, SAR).
 * Familiarity with TorchGeo or TerraTorch.
 * Experience with Rasterio, Geopandas, Xarray, or Dask.
 * Previous collaboration with academic or scientific research communities.
 * Publications in peer-reviewed journals or conferences.

## Description

* Remote-first with flexible working hours, built on trust.
 * Monthly team meetups at a London-based office (Highbury).
 * Clear communication, fast iteration, and support over silos.
 * A culture that thrives on ambiguity, feedback, and a growth mindset.

What You'll Do

 * Design, build, and scale machine learning models using environmental and observational data.
 * Apply advanced causal inference techniques such as Bayesian Neural Networks, Gaussian Processes, Difference-in-Differences, and Synthetic Control methods.
 * Leverage foundation models (e.g. Prithvi, Clay) and transformers to extract insights from complex datasets.
 * Work cross-functionally with science, engineering, and product teams to embed models into real-world pipelines.
 * Communicate scientific and technical concepts clearly to both technical and non-technical audiences.
 * Stay current with the latest developments in AI and environmental science, integrating relevant innovations into production.
 * Mentor junior team members and foster best practices in applied ML.


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